Multiscale Simulation Research Articles

A hybrid atomistic-continuum framework for multiscale simulations of boiling

Boiling is a multiscale physics process where the nucleation of vapour bubbles occurs due to molecular-scale interactions between the fluid and a heated wall, but it also depends on the larger-scale hydrodynamics and thermal boundary layers determined by the outer system boundary conditions. Modelling boiling from the nanometre up to the millimetre scales at which bubble departure occurs is not possible via state-of-the-art simulation methods: Molecular Dynamics (MD) simulations can capture nucleation from first principles but are limited to nanometre scales due to their computational cost, whereas computational fluid dynamics (CFD) simulations based on the continuum Navier-Stokes equations cannot capture nucleation. Here, we present a novel multiscale simulation method which merges MD and CFD descriptions into a single modelling framework, where MD resolves the near-wall region where molecular interactions are important, and a CFD solver resolves the bulk flow. We model the progressive heating of a Lennard-Jones fluid via contact with a solid wall until a vapour bubble nucleates in the MD region of the domain and grows by entering in the CFD domain. Our results show that an incompressible CFD flow model based on the Volume Of Fluid method with interphase mass transfer calculated via the Hertz-Knudsen-Schrage equation is sufficient to obtain seamless coupling of phase fraction, velocity and temperature fields, with the hybrid MD-CFD framework yielding bubble dynamics closely matching those of MD alone.

Multi-scale simulation of typhoon wind field at building scale utilizing mesoscale model with nested large eddy simulation

Based on the mesoscale WRF (Weather Research Forecast) and LES (Large Eddy Simulation), an integrated numerical simulation framework aiming to resolve typhoon wind fields around urban building blocks has been developed. The holistic multi-scale simulation spans four scales: macroscale (∼1000 km), mesoscale (∼100 km), microscale (∼1 km), and building scale (0.1–100m). By interactively sharing the meteorological data among different scales, this simulation framework addressed the challenge of downscaling typhoon effects in urban environments. Typhoon weather reanalysis and urban wind field simulation were conducted by the WRF model with nested computational domains incorporating high-resolution topography data. For the downscaled LES model with urban buildings, the wind profiles produced by the WRF model were used at the interface with provided turbulent fluctuations in the flow. K11 building is a 270-m-tall building located in a densely built-up area of Hong Kong. Wind velocity and pressure fields surrounding the K11 building in Hong Kong during Typhoon Kammuri were obtained by the proposed framework, and the simulation results were validated by comparing with the meteorological data and full-scale measurements at the top of the K11 building. The interactions of the wind fields and building clusters resulting in vortex shedding, separation, and channeling effects have been resolved at high resolutions. Probabilistic distributions and higher-order statistics of wind pressure, i.e., skewness and kurtosis, were presented to highlight non-Gaussian characteristics of the simulated local wind pressure on the K11 building. Based on the simulated wind pressure, wind-induced vibration of the K11 building during the typhoon was analyzed and compared to the measurements.

A microstructure-based graph neural network for accelerating multiscale simulations

Simulating the mechanical response of advanced materials can be done more accurately using concurrent multiscale models than with single-scale simulations. However, the computational costs stand in the way of the practical application of this approach. The costs originate from microscale Finite Element (FE) models that must be solved at every macroscopic integration point. A plethora of surrogate modeling strategies attempt to alleviate this cost by learning to predict macroscopic stresses from macroscopic strains, completely replacing the microscale models. In this work, we introduce an alternative surrogate modeling strategy that allows for keeping the multiscale nature of the problem, allowing it to be used interchangeably with an FE solver for any time step. Our surrogate provides all microscopic quantities, which are then homogenized to obtain macroscopic quantities of interest. We achieve this for an elasto-plastic material by predicting full-field microscopic strains using a graph neural network (GNN) while retaining the microscopic constitutive material model to obtain the stresses. This hybrid data-physics graph-based approach avoids the high dimensionality originating from predicting full-field responses while allowing non-locality to arise. In addition, this approach introduces beneficial inductive bias to the model by encoding microscopic geometrical features. By training the GNN on a variety of meshes, it learns to generalize to unseen meshes, allowing a single model to be used for a range of microstructures. The embedded microscopic constitutive model in the GNN implicitly tracks history-dependent variables and leads to improved accuracy. While the microscopic stresses are fully dependent on the microscopic strains, we found it crucial to include both microscopic strains and stresses in the loss function. We demonstrate for several challenging scenarios that the surrogate can predict complex macroscopic stress–strain paths. As the computation time of our method scales favorably with the number of elements in the microstructure compared to the FE method, our method can significantly accelerate FE2 simulations.

Numerical Coupling between a FEM Code and the FVM Code OpenFOAM Using the MED Library

This paper investigates a numerical code-coupling technique to tackle multiphysics and multiscale simulations using state-of-the-art software packages that typically address some specific modeling domain. The coupling considers the in-house FEM code FEMuS and the FVM code OpenFOAM by exploiting the MED library from the SALOME platform. The present approach is tested on a buoyancy-driven fluid flow within a square cavity, where the buoyancy force constitutes the coupling term. In uncoupled scenarios, momentum and temperature equations are solved in both FEM and FVM codes without data exchange. In the coupled setting, only the OpenFOAM velocity and the FEMuS temperature fields are solved separately and shared at each time step (or vice versa). The MED library handles the coupling with ad hoc data structures that perform the field transfer between codes. Different Rayleigh numbers are investigated, comparing the outcomes of coupled and uncoupled cases with the reference literature results. Additionally, a boundary data transfer application is presented to extend the capabilities of the coupling algorithm to coupled applications with separate domains. In this problem, the two domains share interfaces and boundary values on specific fields as fluxes are exchanged between the two numerical codes.

Multi-scale simulation of microstructural evolution for molten U–Zr–O ternary system

The morphological evolution of the molten corium is critical to the success of the “in-vessel retention” (IVR) strategy, which is of great significance for the safety of the nuclear industry under severe accidents. However, the direct observation of microstructural evolution by experiments is impossible in extreme conditions. Herein, a multi-scale simulation approach was employed to investigate the microstructural evolution and related mechanisms for the molten U–Zr–O ternary system. First, based on the reported calculated phase diagram, a simplified free energy formula describing a phase diagram of U–Zr–O was determined, where only liquid phases are focused. Then, the atomic diffusion coefficients were calculated by ab-initio molecular dynamics simulations. Based on such information, a homemade phase-field model was developed, which was coupled with Cahn–Hillard and Navier–Stokes equations. Accordingly, the microstructural evolution of molten U–Zr–O materials was systematically investigated. The results reveal that the evolution of the molten core was driven by both the decreasing free energy and gravity potential, accessing the final morphology of the system as a two-layer structure, including a metallic layer and an oxidized layer. Moreover, diverse intermediate morphologies could be observed from different initial component distributions, although their average compositions were identical. Finally, some intermediate simulated microstructural patterns agreed well with experimental observation, demonstrating the unstable structures captured by experiments and the validity of the simulations. The present study provides an effective approach to investigate the microstructural evolution of molten core and a guideline for optimizing the IVR strategy based on different morphologies in the corium.

From digital rock to digital wellbore: Multiscale reconstruction and simulation

From digital rock to digital wellbore: Multiscale reconstruction and simulation

Direct FE2 multiscale modeling of hydrogen-induced cracking in reactor pressure vessels

Leveraging on a recently developed multiscale simulation method, we propose a pioneering strategy for the multiscale analysis of hydrogen-induced cracking in reactor pressure vessels that considers micro-voids, their influences on hydrogen diffusion as well as the operating pressure of the vessel. In the finite element analysis, the nodal lattice hydrogen concentration and displacements are exchanged bi-directionally between the macroscale and microscale within a monolithic solution procedure. During the analysis, the voids are shown to cause non-uniform lattice hydrogen diffusion and the trapping effect, resulting in inter-void hydrogen accumulation, is demonstrated. Based on the hydrogen concentration on the void surfaces, the void hydrogen pressure was calculated for the hydrogen-induced cracking analysis. It was found that both internal shearing and necking failure modes exhibited micro-structure dependence. The internal shearing mode caused oriented through-wall propagation of cracks in the vessel pressure while the internal necking mode promoted void nucleation in the reactor pressure vessel. As a result, during the early stages of void evolution, the oriented internal shearing of the dispersed small voids showed a high possibility to induce through-wall failure of the reactor pressure vessel.

Catalytic hydrogenation reaction micro-kinetic model for dibenzyltoluene as liquid organic hydrogen carrier

The implementation of the liquid organic hydrogen carrier (LOHC) technology for efficient energy storage requires the development of a reliable kinetic model for both hydrogenation and dehydrogenation processes. In this research study, the catalytic hydrocarbon saturation for a dibenzyltoluene (DBT) mixture solution, containing dibenzylbenzene (DBB), dibenzylethylbenzene (DBEB) and impurities has been performed in the presence of Ru/Al2O3 particles. The influence of different reaction conditions, such as temperature, pressure, initial reactant concentration, catalyst amount and stirring speed has been examined. A measurement-based system micro-kinetics, based on the Langmuir–Hinshelwood mechanism with dissociative H2 surface adsorption, has been derived. H2 thermodynamic solubility equilibrium was defined through Henry's law. The adsorbing, desorption and reactivity of inert solvent molecules was not considered to be relevant. The mass transfer resistance over 1000 rpm stirring speed was negligible. Relative- and mean squared error of representation were 40.9% and 1.00×10−4, respectively. Expressions gave an excellent data prediction for the profile period trends with a relatively accurate estimation of H2 intermediates' rate selectivity, H2-covered area approximation and pathway rate-determining steps. Due to the lack of commercially available standard chemical compounds for quantitative analysis techniques, a novel experiment-based numerical calibration method was developed. Mean field (micro)kinetics represent an advancement in the mesoscale mechanistic understanding of physical interface phenomena. This also enables catalysis structure–activity relationships, unlocking the methodology for new LOHC reaching beyond traditional, such as ammonia, methanol and formate, which do not release H2 alone. Integrated multiscale simulations could include fluidics later on.

Origami theory-inspired multiscale simulation of folded graphene aerogel with improved mechanical properties

Origami theory-inspired multiscale simulation of folded graphene aerogel with improved mechanical properties

Multiscale simulations of DNA from electrons to nucleosomes: 22years of the Ascona B-DNA Consortium.

This commentary provides a retrospective on the Ascona B-DNA Consortium (ABC) initiative and on the conference held in April 2023 at Ascona, Switzerland, where we celebrated 22years of the consortium, sharing the latest advances in simulations and experiments of the effects of sequence on the mechanical properties of DNA from electrons to nucleosomes.

Multiscale Simulations of Self-Assembling Peptides: Surface and Core Hydrophobicity Determine Fibril Stability and Amyloid Aggregation.

Assemblies of peptides and proteins through specific intermolecular interactions set the basis for macroscopic materials found in nature. Peptides provide easily tunable hydrogen-bonding interactions, which can lead to the formation of ordered structures such as highly stable β-sheets that can form amyloid-like supramolecular peptide nanofibrils (PNFs). PNFs are of special interest, as they could be considered as mimics of various fibrillar structures found in nature. In their ability to serve as supramolecular scaffolds, they could mimic certain features of the extracellular matrix to provide stability, interact with pathogens such as virions, and transduce signals between the outside and inside of cells. Many PNFs have been reported that reveal rich bioactivities. PNFs supporting neuronal cell growth or lentiviral gene transduction have been studied systematically, and their material properties were correlated to bioactivities. However, the impact of the structure of PNFs, their dynamics, and stabilities on their unique functions is still elusive. Herein, we provide a microscopic view of the self-assembled PNFs to unravel how the amino acid sequence of self-assembling peptides affects their secondary structure and dynamic properties of the peptides within supramolecular fibrils. Based on sequence truncation, amino acid substitution, and sequence reordering, we demonstrate that peptide-peptide aggregation propensity is critical to form bioactive β-sheet-rich structures. In contrast to previous studies, a very high peptide aggregation propensity reduces bioactivity due to intermolecular misalignment and instabilities that emerge when fibrils are in close proximity to other fibrils in solution. Our multiscale simulation approach correlates changes in biological activity back to single amino acid modifications. Understanding these relationships could lead to future material discoveries where the molecular sequence predictably determines the macroscopic properties and biological activity. In addition, our studies may provide new insights into naturally occurring amyloid fibrils in neurodegenerative diseases.

μ2mech: A software package combining microstructure modeling and mechanical property prediction

We have developed a graphical user interface (GUI) based package μ2mech to perform phase-field simulation for predicting microstructure evolution. The package can take inputs from ab initio calculations and CALPHAD (Calculation of Phase Diagrams) tools for quantitative microstructure prediction. The package also provides a seamless connection to transfer output from the mesoscale phase field method to the microscale finite element analysis for mechanical property prediction. Such a multiscale simulation package can facilitate microstructure-property correlation, one of the cornerstones in accelerated materials development within the integrated computational materials engineering (ICME) framework.

Nanoparticles as an antidote for poisoned gold single-atom catalysts in sustainable propylene epoxidation

The development of sustainable and anti-poisoning single-atom catalysts (SACs) is essential for advancing their research from laboratory to industry. Here, we present a proof-of-concept study on the poisoning of Au SACs, and the antidote of Au nanoparticles (NPs), with trace addition shown to reinforce and sustain propylene epoxidation. Multiple characterizations, kinetics investigations, and multiscale simulations reveal that Au SACs display remarkable epoxidation activity at a low propylene coverage, but become poisoned at higher coverages. Interestingly, Au NPs can synergistically cooperate with Au SACs by providing distinct active sites required for H2/O2 and C3H6 activations, as well as hydroperoxyl radical to restore poisoned SACs. The difference in reaction order between C3H6 and H2 (nC3H6-nH2) is identified as the descriptor for establishing the volcano curves, which can be fine-tuned by the intimacy and composition of SACs and NPs to achieve a rate-matching scenario for the formation, transfer, and consumption of hydroperoxyl. Consequently, only trace addition of Au NPs antidote (0.3% ratio of SACs) stimulates significant improvements in propylene oxide formation rate, selectivity, and H2 efficiency compared to SACs alone, offering a 56-fold, 3-fold, and 22-fold increase, respectively, whose performances can be maintained for 150 h.

Physicochemical-mechanical simulation of the short- and long-term performance of FRP reinforced concrete beams under marine environments

To broaden the applications of fiber reinforced polymer (FRP) reinforced concrete structures under marine environments, it is crucial to gain a fundamental understanding of their short- and long-term performance. In this study, the effectiveness of the proposed multi-scale simulation platform, which incorporates the proposed degradation model of FRP bars, is quantitatively assessed via the comparison between the predicted results and experimental load-displacement curves under different marine conditions (continuous immersion, wet-dry cycling and subtropical marine atmosphere). The spatially physical, chemical and mechanical information, such as pH value, moisture, hydration degree, strength, porosity during the exposure was also revealed. Finally, the long-term structural performance of FRP-reinforced concrete beams exposed to the predefined environmental conditions over durations of 20, 50 and 100 years are assessed using the multi-scale simulation platform. After 50 years of exposure, the load-bearing capacity of GFRP-reinforced concrete beams was found to decrease by 35.8 % in immersion conditions and by 17.9 % in subtropical marine atmosphere. The degradation of the load-bearing capacity in the case of 100 years exposure to subtropical marine atmosphere was found to be less severe than that (23.1 %) in the case of 50-year immersion. These findings not only deepen our understanding of the material and structural properties of FRP-reinforced concrete beams under various environmental conditions, but also validate the effectiveness of the proposed multi-scale platform.

Multiscale simulation study on radiation aging of EPDM and preparation of radiation-resistant materials

With the wide application of ethylene propylene diene monomer (EPDM) in the field of nuclear engineering, exploring the radiation aging mechanism of EPDM is of great significance to improve the radiation resistance of EPDM composites. In this paper, the radiation aging mechanism of EPDM was investigated by a combination of experiments and multiscale simulations, and EPDM composites with excellent radiation resistance were prepared. The radiation aging mechanism of EPDM involves the crosslinking and degradation of molecular chains. The aging of EPDM starts from the breakage of α-H in the 5-ethylidene-2-norbornene monomer. In addition, the screening strategy of radiation-resistant additives was proposed. Antioxidants N, N′-diphenyl-p-phenylene-diamine (H), N, N′-ditolyl-p-phenylenediamine (DTPD), and N, N′-di-2-naphthyl-p-phenylenediamine (DNP) were taken as the main research objects, and quantitative analysis was carried out from the aspects of chemical protection and physical protection. The screening results showed that DNP has excellent radiation resistance and migration resistance. The prepared EPDM-DNP composites showed outstanding radiation resistance with 94% tensile strength retention after 300 kGy irradiation. This work contributes to understand the mechanisms of radiation-induced material damage and guides the design of radiation-resistant materials.

Accurate and efficient multiscale simulation of a heterogeneous elastic beam via computation on small sparse patches

Modern `smart' materials have complex microscale structure, often with unknown macroscale closure. The Equation-Free Patch Scheme empowers us to non-intrusively, efficiently, and accurately simulate over large scales through computations on only small well-separated patches of the microscale system. Here the microscale system is a solid beam of random heterogeneous elasticity. The continuing challenge is to compute the given physics on just the microscale patches, and couple the patches across un-simulated macroscale space, in order to establish efficiency, accuracy, consistency, and stability on the macroscale. Dynamical systems theory supports the scheme. This research program is to develop a systematic non-intrusive approach, both computationally and analytically proven, to model and compute accurately macroscale system levels of general complex physical and engineering systems.

Accurate prediction of aging effects on microstructure evolution and related mechanical strength of Mg-Zn alloys via multiscale simulations

Age strengthening is a common method to achieve superior mechanical properties employed in magnesium (Mg) alloys. However, the experimental approaches to examine the aging effects on mechanical properties are primarily based on trial and error, posing challenges for the design and development of high-strength Mg alloys. A promising solution to address this challenge is to establish an accurate prediction model for the aging effects on Mg alloys, covering the evolution of microstructure and corresponding mechanical properties. This paper introduces a multiscale simulation approach to accurately predict the aging effects on the Mg-2.3Zn (at.%) alloy. To begin, we establish a phase field model to simulate the microstructure evolution at 150 ℃, demonstrating precipitate growth during aging in alignment with experimental observations. Secondly, based on the microstructures obtained from phase field simulations, the corresponding yield strength is determined through finite element method simulations. The simulation successfully captures the peak-aged behavior of yield strength during aging, resulting in a yield strength of 167 MPa at the peak-aged state, with a deviation of less than 5 % from experimental results. In-depth analysis indicates that the peak value of total yield strength arises from the interplay between solid solution strengthening and precipitate strengthening. Furthermore, precipitate strengthening reaches a peak value at a specific aging time, deviating from the total yield strength. This deviation is primarily attributed to the effect of precipitate size on shear strengthening during aging. This study presents a general method for predicting the microstructure evolution and corresponding mechanical properties of alloys through multiscale simulations, offering valuable insights for designing and predicting the performance of metallic alloys.

State-dependent binding of cholesterol and an anionic lipid to the muscle-type Torpedo nicotinic acetylcholine receptor

The ability of the Torpedo nicotinic acetylcholine receptor (nAChR) to undergo agonist-induced conformational transitions requires the presence of cholesterol and/or anionic lipids. Here we use recently solved structures along with multiscale molecular dynamics simulations to examine lipid binding to the nAChR in bilayers that have defined effects on nAChR function. We examine how phosphatidic acid and cholesterol, lipids that support conformational transitions, individually compete for binding with phosphatidylcholine, a lipid that does not. We also examine how the two lipids work synergistically to stabilize an agonist-responsive nAChR. We identify rapidly exchanging lipid binding sites, including both phospholipid sites with a high affinity for phosphatidic acid and promiscuous cholesterol binding sites in the grooves between adjacent transmembrane α-helices. A high affinity cholesterol site is confirmed in the inner leaflet framed by a key tryptophan residue on the MX α-helix. Our data provide insight into the dynamic nature of lipid-nAChR interactions and set the stage for a detailed understanding of the mechanisms by which lipids facilitate nAChR function at the neuromuscular junction.

Computational Insights into the Conformational Dynamics of HIV-1 Vpr in a Lipid Bilayer for Ion Channel Modeling.

HIV-1 Vpr is a multifunctional accessory protein consisting of 96 amino acids that play a critical role in viral pathogenesis. Among its diverse range of activities, Vpr can create a cation-selective ion channel within the plasma membrane. However, the oligomeric state of this channel has not yet been elucidated. In this study, we investigated the conformational dynamics of Vpr helices to model the ion channel topology. First, we employed a series of multiscale simulations to investigate the specific structure of monomeric Vpr in a membrane model. During the lipid bilayer self-assembly coarse grain simulation, the C-terminal helix (residues 56-77) effectively formed the transmembrane region, while the N-terminal helix exhibited an amphipathic nature by associating horizontally with a single leaflet. All-atom molecular dynamics (MD) simulations of full-length Vpr inside a phospholipid bilayer show that the C-terminal helix remains very stable inside the bilayer core in a vertical orientation. Subsequently, using the predicted C-terminal helix orientation and conformation, various oligomeric states (ranging from tetramer to heptamer) possibly forming the Vpr ion channel were built and further evaluated. Among these models, the pentameric form exhibited consistent stability in MD simulations and displayed a compatible conformation for a water-assisted ion transport mechanism. This study provides structural insights into the ion channel activity of the Vpr protein and the foundation for developing therapeutics against HIV-1 Vpr-related conditions.

Erythritol as a Saccharide Multifunctional Electrolyte Additive for Highly Reversible Zinc Anode.

Dendrite formation and water-triggered side reactions on the surface of Zn metal anodes severely restrict the commercial viability of aqueous zinc-ion batteries (AZIBs). In this work, we introduce erythritol (Et) as an electrolyte additive to enhance the reversibility of zinc anodes, given its cost-effectiveness, mature technology, and extensive utilization in various domains such as food, medicine, and other industries. By combining multiscale theoretical simulation and experimental characterization, it was demonstrated that Et molecules can partially replace the coordination H2O molecules to reshape the Zn2+ solvation sheath and destroy the hydrogen bond network of the aqueous electrolyte. More importantly, Et molecules tend to adsorb on the zinc anode surface, simultaneously inhibit water-triggered side reactions by isolating water and promote uniform and dense deposition by accelerating the Zn2+ diffusion and regulating the nucleation size of the Zn grain. Thanks to this synergistic mechanism, the Zn anode can achieve a cycle life of more than 3900 h at 1 mA cm-2 and an average Coulombic efficiency of 99.77%. Coupling with δ-MnO2 cathodes, the full battery delivers a high specific capacity of 228.1 mAh g-1 with a capacity retention of 76% over 1000 cycles at 1 A g-1.